Apparatus and method for complex by complex conjugate multiplication

ABSTRACT

An apparatus and method for multiplying packed real and imaginary components of complex numbers are described. A processor embodiment includes: a decoder to decode a first instruction to generate a decoded instruction; a first source register to store a first plurality of packed real and imaginary data elements; a second source register to store a second plurality of packed real and imaginary data elements; and execution circuitry to execute the decoded instruction. The execution circuitry includes: multiplier circuitry to select real and imaginary data elements in the first source register and second source, multiply each selected imaginary data element in the first source register with a selected real data element in the second source register, and multiply each selected real data element in the first source register with a selected imaginary data element in the second source register to generate a plurality of imaginary products; adder circuitry to add a first subset of the plurality of imaginary products and subtract a second subset of the plurality of imaginary products to generate a first temporary result, and to add a third subset of the plurality of imaginary products and subtract a fourth subset of the plurality of imaginary products to generate a second temporary result; and accumulation circuitry to combine the first temporary result with first data from a destination register to generate a first final result, combine the second temporary result with second data from the destination register to generate a second final result, and store the first final result and second final result back in the destination register.

BACKGROUND Field of the Invention

The embodiments of the invention relate generally to the field ofcomputer processors. More particularly, the embodiments relate to anapparatus and method for complex by complex conjugate multiplication.

Description of the Related Art

An instruction set, or instruction set architecture (ISA), is the partof the computer architecture related to programming, including thenative data types, instructions, register architecture, addressingmodes, memory architecture, interrupt and exception handling, andexternal input and output (I/O). It should be noted that the term“instruction” generally refers herein to macro-instructions—that isinstructions that are provided to the processor for execution—as opposedto micro-instructions or micro-ops—that is the result of a processor'sdecoder decoding macro-instructions. The micro-instructions or micro-opscan be configured to instruct an execution unit on the processor toperform operations to implement the logic associated with themacro-instruction.

The ISA is distinguished from the microarchitecture, which is the set ofprocessor design techniques used to implement the instruction set.Processors with different microarchitectures can share a commoninstruction set. For example, Intel® Pentium 4 processors, Intel® Core™processors, and processors from Advanced Micro Devices, Inc. ofSunnyvale Calif. implement nearly identical versions of the x86instruction set (with some extensions that have been added with newerversions), but have different internal designs. For example, the sameregister architecture of the ISA may be implemented in different ways indifferent microarchitectures using well-known techniques, includingdedicated physical registers, one or more dynamically allocated physicalregisters using a register renaming mechanism (e.g., the use of aRegister Alias Table (RAT), a Reorder Buffer (ROB) and a retirementregister file). Unless otherwise specified, the phrases registerarchitecture, register file, and register are used herein to refer tothat which is visible to the software/programmer and the manner in whichinstructions specify registers. Where a distinction is required, theadjective “logical,” “architectural,” or “software visible” will be usedto indicate registers/files in the register architecture, whiledifferent adjectives will be used to designate registers in a givenmicroarchitecture (e.g., physical register, reorder buffer, retirementregister, register pool).

Multiply-accumulate is a common digital signal processing operationwhich computes the product of two numbers and adds that product to anaccumulated value. Existing single instruction multiple data (SIMD)microarchitectures implement multiply-accumulate operations by executinga sequence of instructions. For example, a multiply-accumulate may beperformed with a multiply instruction, followed by a 4-way addition, andthen an accumulation with the destination quadword data to generate two64-bit saturated results.

BRIEF DESCRIPTION OF THE DRAWINGS

A better understanding of the present invention can be obtained from thefollowing detailed description in conjunction with the followingdrawings, in which:

FIGS. 1A and 1B are block diagrams illustrating a generic vectorfriendly instruction format and instruction templates thereof accordingto embodiments of the invention;

FIGS. 2A-C are block diagrams illustrating an exemplary VEX instructionformat according to embodiments of the invention;

FIG. 3 is a block diagram of a register architecture according to oneembodiment of the invention; and

FIG. 4A is a block diagram illustrating both an exemplary in-orderfetch, decode, retire pipeline and an exemplary register renaming,out-of-order issue/execution pipeline according to embodiments of theinvention;

FIG. 4B is a block diagram illustrating both an exemplary embodiment ofan in-order fetch, decode, retire core and an exemplary registerrenaming, out-of-order issue/execution architecture core to be includedin a processor according to embodiments of the invention;

FIG. 5A is a block diagram of a single processor core, along with itsconnection to an on-die interconnect network;

FIG. 5B illustrates an expanded view of part of the processor core inFIG. 5A according to embodiments of the invention;

FIG. 6 is a block diagram of a single core processor and a multicoreprocessor with integrated memory controller and graphics according toembodiments of the invention;

FIG. 7 illustrates a block diagram of a system in accordance with oneembodiment of the present invention;

FIG. 8 illustrates a block diagram of a second system in accordance withan embodiment of the present invention;

FIG. 9 illustrates a block diagram of a third system in accordance withan embodiment of the present invention;

FIG. 10 illustrates a block diagram of a system on a chip (SoC) inaccordance with an embodiment of the present invention;

FIG. 11 illustrates a block diagram contrasting the use of a softwareinstruction converter to convert binary instructions in a sourceinstruction set to binary instructions in a target instruction setaccording to embodiments of the invention;

FIG. 12 illustrates a processor architecture on which embodiments of theinvention may be implemented;

FIG. 13 illustrates a plurality of packed data elements containing realand complex values in accordance with one embodiment;

FIG. 14A-B illustrate different architectures on which embodiments ofthe invention may be implemented;

FIG. 15 illustrates a method in accordance with one embodiment of theinvention;

FIG. 16 illustrates a method in accordance with another embodiment ofthe invention.

DETAILED DESCRIPTION

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the embodiments of the invention described below. Itwill be apparent, however, to one skilled in the art that theembodiments of the invention may be practiced without some of thesespecific details. In other instances, well-known structures and devicesare shown in block diagram form to avoid obscuring the underlyingprinciples of the embodiments of the invention.

Exemplary Processor Architectures, Instruction Formats, and Data Types

An instruction set includes one or more instruction formats. A giveninstruction format defines various fields (number of bits, location ofbits) to specify, among other things, the operation to be performed(opcode) and the operand(s) on which that operation is to be performed.Some instruction formats are further broken down though the definitionof instruction templates (or subformats). For example, the instructiontemplates of a given instruction format may be defined to have differentsubsets of the instruction format's fields (the included fields aretypically in the same order, but at least some have different bitpositions because there are less fields included) and/or defined to havea given field interpreted differently. Thus, each instruction of an ISAis expressed using a given instruction format (and, if defined, in agiven one of the instruction templates of that instruction format) andincludes fields for specifying the operation and the operands. Forexample, an exemplary ADD instruction has a specific opcode and aninstruction format that includes an opcode field to specify that opcodeand operand fields to select operands (source1/destination and source2);and an occurrence of this ADD instruction in an instruction stream willhave specific contents in the operand fields that select specificoperands.

Embodiments of the instruction(s) described herein may be embodied indifferent formats. Additionally, exemplary systems, architectures, andpipelines are detailed below. Embodiments of the instruction(s) may beexecuted on such systems, architectures, and pipelines, but are notlimited to those detailed.

Generic Vector Friendly Instruction Format

A vector friendly instruction format is an instruction format that issuited for vector instructions (e.g., there are certain fields specificto vector operations). While embodiments are described in which bothvector and scalar operations are supported through the vector friendlyinstruction format, alternative embodiments use only vector operationsthe vector friendly instruction format.

FIGS. 1A-1B are block diagrams illustrating a generic vector friendlyinstruction format and instruction templates thereof according toembodiments of the invention. FIG. 1A is a block diagram illustrating ageneric vector friendly instruction format and class A instructiontemplates thereof according to embodiments of the invention; while FIG.1B is a block diagram illustrating the generic vector friendlyinstruction format and class B instruction templates thereof accordingto embodiments of the invention. Specifically, a generic vector friendlyinstruction format 100 for which are defined class A and class Binstruction templates, both of which include no memory access 105instruction templates and memory access 120 instruction templates. Theterm generic in the context of the vector friendly instruction formatrefers to the instruction format not being tied to any specificinstruction set.

While embodiments of the invention will be described in which the vectorfriendly instruction format supports the following: a 64-byte vectoroperand length (or size) with 32-bit (4-byte) or 64-bit (8-byte) dataelement widths (or sizes) (and thus, a 64-byte vector consists of either16 doubleword-size elements or alternatively, 8 quadword-size elements);a 64-byte vector operand length (or size) with 16-bit (2-byte) or 8-bit(1-byte) data element widths (or sizes); a 32-byte vector operand length(or size) with 32-bit (4-byte), 64-bit (8-byte), 16-bit (2-byte), or8-bit (1-byte) data element widths (or sizes); and a 16 byte vectoroperand length (or size) with 32-bit (4-byte), 64-bit (8-byte), 16-bit(2-byte), or 8-bit (1-byte) data element widths (or sizes); alternativeembodiments may support more, less and/or different vector operand sizes(e.g., 256-byte vector operands) with more, less, or different dataelement widths (e.g., 128-bit (16-byte) data element widths).

The class A instruction templates in FIG. 1A include: 1) within the nomemory access 105 instruction templates there is shown a no memoryaccess, full round control type operation 110 instruction template and ano memory access, data transform type operation 115 instructiontemplate; and 2) within the memory access 120 instruction templatesthere is shown a memory access, temporal 125 instruction template and amemory access, non-temporal 130 instruction template. The class Binstruction templates in FIG. 1B include: 1) within the no memory access105 instruction templates there is shown a no memory access, write maskcontrol, partial round control type operation 112 instruction templateand a no memory access, write mask control, vsize type operation 117instruction template; and 2) within the memory access 120 instructiontemplates there is shown a memory access, write mask control 127instruction template.

The generic vector friendly instruction format 100 includes thefollowing fields listed below in the order illustrated in FIGS. 1A-1B.

Format field 140—a specific value (an instruction format identifiervalue) in this field uniquely identifies the vector friendly instructionformat, and thus occurrences of instructions in the vector friendlyinstruction format in instruction streams. As such, this field isoptional in the sense that it is not needed for an instruction set thathas only the generic vector friendly instruction format.

Base operation field 142—its content distinguishes different baseoperations.

Register index field 144—its content, directly or through addressgeneration, specifies the locations of the source and destinationoperands, be they in registers or in memory. These include a sufficientnumber of bits to select N registers from a P×Q (e.g. 32×512, 16×128,32×1024, 64×1024) register file. While in one embodiment N may be up tothree sources and one destination register, alternative embodiments maysupport more or less sources and destination registers (e.g., maysupport up to two sources where one of these sources also acts as thedestination, may support up to three sources where one of these sourcesalso acts as the destination, may support up to two sources and onedestination).

Modifier field 146—its content distinguishes occurrences of instructionsin the generic vector instruction format that specify memory access 146Bfrom those that do not 146A; that is, between no memory access 105instruction templates and memory access 120 instruction templates.Memory access operations read and/or write to the memory hierarchy (insome cases specifying the source and/or destination addresses usingvalues in registers), while non-memory access operations do not (e.g.,the source and destinations are registers). While in one embodiment thisfield also selects between three different ways to perform memoryaddress calculations, alternative embodiments may support more, less, ordifferent ways to perform memory address calculations.

Augmentation operation field 150—its content distinguishes which one ofa variety of different operations to be performed in addition to thebase operation. This field is context specific. In one embodiment of theinvention, this field is divided into a class field 168, an alpha field152, and a beta field 154. The augmentation operation field 150 allowscommon groups of operations to be performed in a single instructionrather than 2, 3, or 4 instructions.

Scale field 160—its content allows for the scaling of the index field'scontent for memory address generation (e.g., for address generation thatuses 2^(scale)*index+base).

Displacement Field 162A—its content is used as part of memory addressgeneration (e.g., for address generation that uses2^(scale)*index+base+displacement).

Displacement Factor Field 162B (note that the juxtaposition ofdisplacement field 162A directly over displacement factor field 162Bindicates one or the other is used)—its content is used as part ofaddress generation; it specifies a displacement factor that is to bescaled by the size of a memory access (N)—where N is the number of bytesin the memory access (e.g., for address generation that uses2^(scale)*index+base+scaled displacement). Redundant low-order bits areignored and hence, the displacement factor field's content is multipliedby the memory operands total size (N) in order to generate the finaldisplacement to be used in calculating an effective address. The valueof N is determined by the processor hardware at runtime based on thefull opcode field 174 (described later herein) and the data manipulationfield 154C. The displacement field 162A and the displacement factorfield 162B are optional in the sense that they are not used for the nomemory access 105 instruction templates and/or different embodiments mayimplement only one or none of the two.

Data element width field 164—its content distinguishes which one of anumber of data element widths is to be used (in some embodiments for allinstructions; in other embodiments for only some of the instructions).This field is optional in the sense that it is not needed if only onedata element width is supported and/or data element widths are supportedusing some aspect of the opcodes.

Write mask field 170—its content controls, on a per data elementposition basis, whether that data element position in the destinationvector operand reflects the result of the base operation andaugmentation operation. Class A instruction templates supportmerging-writemasking, while class B instruction templates support bothmerging- and zeroing-writemasking. When merging, vector masks allow anyset of elements in the destination to be protected from updates duringthe execution of any operation (specified by the base operation and theaugmentation operation); in other one embodiment, preserving the oldvalue of each element of the destination where the corresponding maskbit has a 0. In contrast, when zeroing vector masks allow any set ofelements in the destination to be zeroed during the execution of anyoperation (specified by the base operation and the augmentationoperation); in one embodiment, an element of the destination is set to 0when the corresponding mask bit has a 0 value. A subset of thisfunctionality is the ability to control the vector length of theoperation being performed (that is, the span of elements being modified,from the first to the last one); however, it is not necessary that theelements that are modified be consecutive. Thus, the write mask field170 allows for partial vector operations, including loads, stores,arithmetic, logical, etc. While embodiments of the invention aredescribed in which the write mask field's 170 content selects one of anumber of write mask registers that contains the write mask to be used(and thus the write mask field's 170 content indirectly identifies thatmasking to be performed), alternative embodiments instead or additionalallow the mask write field's 170 content to directly specify the maskingto be performed.

Immediate field 172—its content allows for the specification of animmediate. This field is optional in the sense that is it not present inan implementation of the generic vector friendly format that does notsupport immediate and it is not present in instructions that do not usean immediate.

Class field 168—its content distinguishes between different classes ofinstructions. With reference to FIGS. 1A-B, the contents of this fieldselect between class A and class B instructions. In FIGS. 1A-B, roundedcorner squares are used to indicate a specific value is present in afield (e.g., class A 168A and class B 168B for the class field 168respectively in FIGS. 1A-B).

Instruction Templates of Class A

In the case of the non-memory access 105 instruction templates of classA, the alpha field 152 is interpreted as an RS field 152A, whose contentdistinguishes which one of the different augmentation operation typesare to be performed (e.g., round 152A.1 and data transform 152A.2 arerespectively specified for the no memory access, round type operation110 and the no memory access, data transform type operation 115instruction templates), while the beta field 154 distinguishes which ofthe operations of the specified type is to be performed. In the nomemory access 105 instruction templates, the scale field 160, thedisplacement field 162A, and the displacement scale field 162B are notpresent.

No-Memory Access Instruction Templates—Full Round Control Type Operation

In the no memory access full round control type operation 110instruction template, the beta field 154 is interpreted as a roundcontrol field 154A, whose content(s) provide static rounding. While inthe described embodiments of the invention the round control field 154Aincludes a suppress all floating point exceptions (SAE) field 156 and around operation control field 158, alternative embodiments may supportmay encode both these concepts into the same field or only have one orthe other of these concepts/fields (e.g., may have only the roundoperation control field 158).

SAE field 156—its content distinguishes whether or not to disable theexception event reporting; when the SAE field's 156 content indicatessuppression is enabled, a given instruction does not report any kind offloating-point exception flag and does not raise any floating pointexception handler.

Round operation control field 158—its content distinguishes which one ofa group of rounding operations to perform (e.g., Round-up, Round-down,Round-towards-zero and Round-to-nearest). Thus, the round operationcontrol field 158 allows for the changing of the rounding mode on a perinstruction basis. In one embodiment of the invention where a processorincludes a control register for specifying rounding modes, the roundoperation control field's 158 content overrides that register value.

No Memory Access Instruction Templates—Data Transform Type Operation

In the no memory access data transform type operation 115 instructiontemplate, the beta field 154 is interpreted as a data transform field154B, whose content distinguishes which one of a number of datatransforms is to be performed (e.g., no data transform, swizzle,broadcast).

In the case of a memory access 120 instruction template of class A, thealpha field 152 is interpreted as an eviction hint field 152B, whosecontent distinguishes which one of the eviction hints is to be used (inFIG. 1A, temporal 152B.1 and non-temporal 152B.2 are respectivelyspecified for the memory access, temporal 125 instruction template andthe memory access, non-temporal 130 instruction template), while thebeta field 154 is interpreted as a data manipulation field 154C, whosecontent distinguishes which one of a number of data manipulationoperations (also known as primitives) is to be performed (e.g., nomanipulation; broadcast; up conversion of a source; and down conversionof a destination). The memory access 120 instruction templates includethe scale field 160, and optionally the displacement field 162A or thedisplacement scale field 162B.

Vector memory instructions perform vector loads from and vector storesto memory, with conversion support. As with regular vector instructions,vector memory instructions transfer data from/to memory in a dataelement-wise fashion, with the elements that are actually transferred isdictated by the contents of the vector mask that is selected as thewrite mask.

Memory Access Instruction Templates—Temporal

Temporal data is data likely to be reused soon enough to benefit fromcaching. This is, however, a hint, and different processors mayimplement it in different ways, including ignoring the hint entirely.

Memory Access Instruction Templates—Non-Temporal

Non-temporal data is data unlikely to be reused soon enough to benefitfrom caching in the 1st-level cache and should be given priority foreviction. This is, however, a hint, and different processors mayimplement it in different ways, including ignoring the hint entirely.

Instruction Templates of Class B

In the case of the instruction templates of class B, the alpha field 152is interpreted as a write mask control (Z) field 152C, whose contentdistinguishes whether the write masking controlled by the write maskfield 170 should be a merging or a zeroing.

In the case of the non-memory access 105 instruction templates of classB, part of the beta field 154 is interpreted as an RL field 157A, whosecontent distinguishes which one of the different augmentation operationtypes are to be performed (e.g., round 157A.1 and vector length (VSIZE)157A.2 are respectively specified for the no memory access, write maskcontrol, partial round control type operation 112 instruction templateand the no memory access, write mask control, VSIZE type operation 117instruction template), while the rest of the beta field 154distinguishes which of the operations of the specified type is to beperformed. In the no memory access 105 instruction templates, the scalefield 160, the displacement field 162A, and the displacement scale field162B are not present.

In the no memory access, write mask control, partial round control typeoperation 110 instruction template, the rest of the beta field 154 isinterpreted as a round operation field 159A and exception eventreporting is disabled (a given instruction does not report any kind offloating-point exception flag and does not raise any floating pointexception handler).

Round operation control field 159A—just as round operation control field158, its content distinguishes which one of a group of roundingoperations to perform (e.g., Round-up, Round-down, Round-towards-zeroand Round-to-nearest). Thus, the round operation control field 159Aallows for the changing of the rounding mode on a per instruction basis.In one embodiment of the invention where a processor includes a controlregister for specifying rounding modes, the round operation controlfield's 159A content overrides that register value.

In the no memory access, write mask control, VSIZE type operation 117instruction template, the rest of the beta field 154 is interpreted as avector length field 159B, whose content distinguishes which one of anumber of data vector lengths is to be performed on (e.g., 128-, 256-,or 512-byte).

In the case of a memory access 120 instruction template of class B, partof the beta field 154 is interpreted as a broadcast field 157B, whosecontent distinguishes whether or not the broadcast type datamanipulation operation is to be performed, while the rest of the betafield 154 is interpreted the vector length field 159B. The memory access120 instruction templates include the scale field 160, and optionallythe displacement field 162A or the displacement scale field 162B.

With regard to the generic vector friendly instruction format 100, afull opcode field 174 is shown including the format field 140, the baseoperation field 142, and the data element width field 164. While oneembodiment is shown where the full opcode field 174 includes all ofthese fields, the full opcode field 174 includes less than all of thesefields in embodiments that do not support all of them. The full opcodefield 174 provides the operation code (opcode).

The augmentation operation field 150, the data element width field 164,and the write mask field 170 allow these features to be specified on aper instruction basis in the generic vector friendly instruction format.

The combination of write mask field and data element width field createtyped instructions in that they allow the mask to be applied based ondifferent data element widths.

The various instruction templates found within class A and class B arebeneficial in different situations. In some embodiments of theinvention, different processors or different cores within a processormay support only class A, only class B, or both classes. For instance, ahigh performance general purpose out-of-order core intended forgeneral-purpose computing may support only class B, a core intendedprimarily for graphics and/or scientific (throughput) computing maysupport only class A, and a core intended for both may support both (ofcourse, a core that has some mix of templates and instructions from bothclasses but not all templates and instructions from both classes iswithin the purview of the invention). Also, a single processor mayinclude multiple cores, all of which support the same class or in whichdifferent cores support different classes. For instance, in a processorwith separate graphics and general purpose cores, one of the graphicscores intended primarily for graphics and/or scientific computing maysupport only class A, while one or more of the general purpose cores maybe high performance general purpose cores with out of order executionand register renaming intended for general-purpose computing thatsupport only class B. Another processor that does not have a separategraphics core, may include one more general purpose in-order orout-of-order cores that support both class A and class B. Of course,features from one class may also be implemented in another class indifferent embodiments of the invention. Programs written in a high levellanguage would be put (e.g., just in time compiled or staticallycompiled) into an variety of different executable forms, including: 1) aform having only instructions of the class(es) supported by the targetprocessor for execution; or 2) a form having alternative routineswritten using different combinations of the instructions of all classesand having control flow code that selects the routines to execute basedon the instructions supported by the processor which is currentlyexecuting the code.

VEX Instruction Format

VEX encoding allows instructions to have more than two operands, andallows SIMD vector registers to be longer than 28 bits. The use of a VEXprefix provides for three-operand (or more) syntax. For example,previous two-operand instructions performed operations such as A=A+B,which overwrites a source operand. The use of a VEX prefix enablesoperands to perform nondestructive operations such as A=B+C.

FIG. 2A illustrates an exemplary AVX instruction format including a VEXprefix 202, real opcode field 230, Mod R/M byte 240, SIB byte 250,displacement field 262, and IMM8 272. FIG. 2B illustrates which fieldsfrom FIG. 2A make up a full opcode field 274 and a base operation field241. FIG. 2C illustrates which fields from FIG. 2A make up a registerindex field 244.

VEX Prefix (Bytes 0-2) 202 is encoded in a three-byte form. The firstbyte is the Format Field 290 (VEX Byte 0, bits [7:0]), which contains anexplicit C4 byte value (the unique value used for distinguishing the C4instruction format). The second-third bytes (VEX Bytes 1-2) include anumber of bit fields providing specific capability. Specifically, REXfield 205 (VEX Byte 1, bits [7-5]) consists of a VEX.R bit field (VEXByte 1, bit [7]-R), VEX.X bit field (VEX byte 1, bit [6]-X), and VEX.Bbit field (VEX byte 1, bit[5]-B). Other fields of the instructionsencode the lower three bits of the register indexes as is known in theart (rrr, xxx, and bbb), so that Rrrr, Xxxx, and Bbbb may be formed byadding VEX.R, VEX.X, and VEX.B. Opcode map field 215 (VEX byte 1, bits[4:0]-mmmmm) includes content to encode an implied leading opcode byte.W Field 264 (VEX byte 2, bit [7]-W)—is represented by the notationVEX.W, and provides different functions depending on the instruction.The role of VEX.vvvv 220 (VEX Byte 2, bits [6:3]-vvvv) may include thefollowing: 1) VEX.vvvv encodes the first source register operand,specified in inverted (1s complement) form and is valid for instructionswith 2 or more source operands; 2) VEX.vvvv encodes the destinationregister operand, specified in is complement form for certain vectorshifts; or 3) VEX.vvvv does not encode any operand, the field isreserved and should contain 1111b. If VEX.L 268 Size field (VEX byte 2,bit [2]-L)=0, it indicates 28 bit vector; if VEX.L=1, it indicates 256bit vector. Prefix encoding field 225 (VEX byte 2, bits [1:0]-pp)provides additional bits for the base operation field 241.

Real Opcode Field 230 (Byte 3) is also known as the opcode byte. Part ofthe opcode is specified in this field.

MOD R/M Field 240 (Byte 4) includes MOD field 242 (bits [7-6]), Regfield 244 (bits [5-3]), and R/M field 246 (bits [2-0]). The role of Regfield 244 may include the following: encoding either the destinationregister operand or a source register operand (the rrr of Rrrr), or betreated as an opcode extension and not used to encode any instructionoperand. The role of R/M field 246 may include the following: encodingthe instruction operand that references a memory address, or encodingeither the destination register operand or a source register operand.

Scale, Index, Base (SIB)—The content of Scale field 250 (Byte 5)includes SS 252 (bits [7-6]), which is used for memory addressgeneration. The contents of SIB.xxx 254 (bits [5-3]) and SIB.bbb 256(bits [2-0]) have been previously referred to with regard to theregister indexes Xxxx and Bbbb.

The Displacement Field 262 and the immediate field (IMM8) 272 containdata.

Exemplary Register Architecture

FIG. 3 is a block diagram of a register architecture 300 according toone embodiment of the invention. In the embodiment illustrated, thereare 32 vector registers 310 that are 512 bits wide; these registers arereferenced as zmm0 through zmm31. The lower order 256 bits of the lower16 zmm registers are overlaid on registers ymm0-15. The lower order 128bits of the lower 16 zmm registers (the lower order 128 bits of the ymmregisters) are overlaid on registers xmm0-15.

General-purpose registers 325—in the embodiment illustrated, there aresixteen 64-bit general-purpose registers that are used along with theexisting x86 addressing modes to address memory operands. Theseregisters are referenced by the names RAX, RBX, RCX, RDX, RBP, RSI, RDI,RSP, and R8 through R15.

Scalar floating point stack register file (x87 stack) 345, on which isaliased the MMX packed integer flat register file 350—in the embodimentillustrated, the x87 stack is an eight-element stack used to performscalar floating-point operations on 32/64/80-bit floating point datausing the x87 instruction set extension; while the MMX registers areused to perform operations on 64-bit packed integer data, as well as tohold operands for some operations performed between the MMX and XMMregisters.

Alternative embodiments of the invention may use wider or narrowerregisters. Additionally, alternative embodiments of the invention mayuse more, less, or different register files and registers.

Exemplary Core Architectures, Processors, and Computer Architectures

Processor cores may be implemented in different ways, for differentpurposes, and in different processors. For instance, implementations ofsuch cores may include: 1) a general purpose in-order core intended forgeneral-purpose computing; 2) a high performance general purposeout-of-order core intended for general-purpose computing; 3) a specialpurpose core intended primarily for graphics and/or scientific(throughput) computing. Implementations of different processors mayinclude: 1) a CPU including one or more general purpose in-order coresintended for general-purpose computing and/or one or more generalpurpose out-of-order cores intended for general-purpose computing; and2) a coprocessor including one or more special purpose cores intendedprimarily for graphics and/or scientific (throughput) computing. Suchdifferent processors lead to different computer system architectures,which may include: 1) the coprocessor on a separate chip from the CPU;2) the coprocessor on a separate die in the same package as a CPU; 3)the coprocessor on the same die as a CPU (in which case, such acoprocessor is sometimes referred to as special purpose logic, such asintegrated graphics and/or scientific (throughput) logic, or as specialpurpose cores); and 4) a system on a chip that may include on the samedie the described CPU (sometimes referred to as the application core(s)or application processor(s)), the above described coprocessor, andadditional functionality. Exemplary core architectures are describednext, followed by descriptions of exemplary processors and computerarchitectures. Detailed herein are circuits (units) that compriseexemplary cores, processors, etc.

Exemplary Core Architectures

FIG. 4A is a block diagram illustrating both an exemplary in-orderpipeline and an exemplary register renaming, out-of-orderissue/execution pipeline according to embodiments of the invention. FIG.4B is a block diagram illustrating both an exemplary embodiment of anin-order architecture core and an exemplary register renaming,out-of-order issue/execution architecture core to be included in aprocessor according to embodiments of the invention. The solid linedboxes in FIGS. 4A-B illustrate the in-order pipeline and in-order core,while the optional addition of the dashed lined boxes illustrates theregister renaming, out-of-order issue/execution pipeline and core. Giventhat the in-order aspect is a subset of the out-of-order aspect, theout-of-order aspect will be described.

In FIG. 4A, a processor pipeline 400 includes a fetch stage 402, alength decode stage 404, a decode stage 406, an allocation stage 408, arenaming stage 410, a scheduling (also known as a dispatch or issue)stage 412, a register read/memory read stage 414, an execute stage 416,a write back/memory write stage 418, an exception handling stage 422,and a commit stage 424.

FIG. 4B shows processor core 490 including a front end unit 430 coupledto an execution engine unit 450, and both are coupled to a memory unit470. The core 490 may be a reduced instruction set computing (RISC)core, a complex instruction set computing (CISC) core, a very longinstruction word (VLIW) core, or a hybrid or alternative core type. Asyet another option, the core 490 may be a special-purpose core, such as,for example, a network or communication core, compression engine,coprocessor core, general purpose computing graphics processing unit(GPGPU) core, graphics core, or the like.

The front end unit 430 includes a branch prediction unit 432 coupled toan instruction cache unit 434, which is coupled to an instructiontranslation lookaside buffer (TLB) 436, which is coupled to aninstruction fetch unit 438, which is coupled to a decode unit 440. Thedecode unit 440 (or decoder) may decode instructions, and generate as anoutput one or more micro-operations, micro-code entry points,microinstructions, other instructions, or other control signals, whichare decoded from, or which otherwise reflect, or are derived from, theoriginal instructions. The decode unit 440 may be implemented usingvarious different mechanisms. Examples of suitable mechanisms include,but are not limited to, look-up tables, hardware implementations,programmable logic arrays (PLAs), microcode read only memories (ROMs),etc. In one embodiment, the core 490 includes a microcode ROM or othermedium that stores microcode for certain macroinstructions (e.g., indecode unit 440 or otherwise within the front end unit 430). The decodeunit 440 is coupled to a rename/allocator unit 452 in the executionengine unit 450.

The execution engine unit 450 includes the rename/allocator unit 452coupled to a retirement unit 454 and a set of one or more schedulerunit(s) 456. The scheduler unit(s) 456 represents any number ofdifferent schedulers, including reservations stations, centralinstruction window, etc. The scheduler unit(s) 456 is coupled to thephysical register file(s) unit(s) 458. Each of the physical registerfile(s) units 458 represents one or more physical register files,different ones of which store one or more different data types, such asscalar integer, scalar floating point, packed integer, packed floatingpoint, vector integer, vector floating point, status (e.g., aninstruction pointer that is the address of the next instruction to beexecuted), etc. In one embodiment, the physical register file(s) unit458 comprises a vector registers unit and a scalar registers unit. Theseregister units may provide architectural vector registers, vector maskregisters, and general purpose registers. The physical register file(s)unit(s) 458 is overlapped by the retirement unit 454 to illustratevarious ways in which register renaming and out-of-order execution maybe implemented (e.g., using a reorder buffer(s) and a retirementregister file(s); using a future file(s), a history buffer(s), and aretirement register file(s); using a register map and a pool ofregisters; etc.). The retirement unit 454 and the physical registerfile(s) unit(s) 458 are coupled to the execution cluster(s) 460. Theexecution cluster(s) 460 includes a set of one or more execution units462 and a set of one or more memory access units 464. The executionunits 462 may perform various operations (e.g., shifts, addition,subtraction, multiplication) and on various types of data (e.g., scalarfloating point, packed integer, packed floating point, vector integer,vector floating point). While some embodiments may include a number ofexecution units dedicated to specific functions or sets of functions,other embodiments may include only one execution unit or multipleexecution units that all perform all functions. The scheduler unit(s)456, physical register file(s) unit(s) 458, and execution cluster(s) 460are shown as being possibly plural because certain embodiments createseparate pipelines for certain types of data/operations (e.g., a scalarinteger pipeline, a scalar floating point/packed integer/packed floatingpoint/vector integer/vector floating point pipeline, and/or a memoryaccess pipeline that each have their own scheduler unit, physicalregister file(s) unit, and/or execution cluster—and in the case of aseparate memory access pipeline, certain embodiments are implemented inwhich only the execution cluster of this pipeline has the memory accessunit(s) 464). It should also be understood that where separate pipelinesare used, one or more of these pipelines may be out-of-orderissue/execution and the rest in-order.

The set of memory access units 464 is coupled to the memory unit 470,which includes a data TLB unit 472 coupled to a data cache unit 474coupled to a level 2 (L2) cache unit 476. In one exemplary embodiment,the memory access units 464 may include a load unit, a store addressunit, and a store data unit, each of which is coupled to the data TLBunit 472 in the memory unit 470. The instruction cache unit 434 isfurther coupled to a level 2 (L2) cache unit 476 in the memory unit 470.The L2 cache unit 476 is coupled to one or more other levels of cacheand eventually to a main memory.

By way of example, the exemplary register renaming, out-of-orderissue/execution core architecture may implement the pipeline 400 asfollows: 1) the instruction fetch 438 performs the fetch and lengthdecoding stages 402 and 404; 2) the decode unit 440 performs the decodestage 406; 3) the rename/allocator unit 452 performs the allocationstage 408 and renaming stage 410; 4) the scheduler unit(s) 456 performsthe schedule stage 412; 5) the physical register file(s) unit(s) 458 andthe memory unit 470 perform the register read/memory read stage 414; theexecution cluster 460 perform the execute stage 416; 6) the memory unit470 and the physical register file(s) unit(s) 458 perform the writeback/memory write stage 418; 7) various units may be involved in theexception handling stage 422; and 8) the retirement unit 454 and thephysical register file(s) unit(s) 458 perform the commit stage 424.

The core 490 may support one or more instructions sets (e.g., the x86instruction set (with some extensions that have been added with newerversions); the MIPS instruction set of MIPS Technologies of Sunnyvale,Calif.; the ARM instruction set (with optional additional extensionssuch as NEON) of ARM Holdings of Sunnyvale, Calif.), including theinstruction(s) described herein. In one embodiment, the core 490includes logic to support a packed data instruction set extension (e.g.,AVX1, AVX2), thereby allowing the operations used by many multimediaapplications to be performed using packed data.

It should be understood that the core may support multithreading(executing two or more parallel sets of operations or threads), and maydo so in a variety of ways including time sliced multithreading,simultaneous multithreading (where a single physical core provides alogical core for each of the threads that physical core issimultaneously multithreading), or a combination thereof (e.g., timesliced fetching and decoding and simultaneous multithreading thereaftersuch as in the Intel® Hyperthreading technology).

While register renaming is described in the context of out-of-orderexecution, it should be understood that register renaming may be used inan in-order architecture. While the illustrated embodiment of theprocessor also includes separate instruction and data cache units434/474 and a shared L2 cache unit 476, alternative embodiments may havea single internal cache for both instructions and data, such as, forexample, a Level 1 (L1) internal cache, or multiple levels of internalcache. In some embodiments, the system may include a combination of aninternal cache and an external cache that is external to the core and/orthe processor. Alternatively, all of the cache may be external to thecore and/or the processor.

Specific Exemplary In-Order Core Architecture

FIGS. 5A-B illustrate a block diagram of a more specific exemplaryin-order core architecture, which core would be one of several logicblocks (including other cores of the same type and/or different types)in a chip. The logic blocks communicate through a high-bandwidthinterconnect network (e.g., a ring network) with some fixed functionlogic, memory I/O interfaces, and other necessary I/O logic, dependingon the application.

FIG. 5A is a block diagram of a single processor core, along with itsconnection to the on-die interconnect network 502 and with its localsubset of the Level 2 (L2) cache 504, according to embodiments of theinvention. In one embodiment, an instruction decoder 500 supports thex86 instruction set with a packed data instruction set extension. An L1cache 506 allows low-latency accesses to cache memory into the scalarand vector units. While in one embodiment (to simplify the design), ascalar unit 508 and a vector unit 510 use separate register sets(respectively, scalar registers 512 and vector registers 514) and datatransferred between them is written to memory and then read back in froma level 1 (L1) cache 506, alternative embodiments of the invention mayuse a different approach (e.g., use a single register set or include acommunication path that allow data to be transferred between the tworegister files without being written and read back).

The local subset of the L2 cache 504 is part of a global L2 cache thatis divided into separate local subsets, one per processor core. Eachprocessor core has a direct access path to its own local subset of theL2 cache 504. Data read by a processor core is stored in its L2 cachesubset 504 and can be accessed quickly, in parallel with other processorcores accessing their own local L2 cache subsets. Data written by aprocessor core is stored in its own L2 cache subset 504 and is flushedfrom other subsets, if necessary. The ring network ensures coherency forshared data. The ring network is bi-directional to allow agents such asprocessor cores, L2 caches and other logic blocks to communicate witheach other within the chip. Each ring data-path is 1024 bits wide perdirection in some embodiments.

FIG. 5B is an expanded view of part of the processor core in FIG. 5Aaccording to embodiments of the invention. FIG. 5B includes an L1 datacache 506A part of the L1 cache 506, as well as more detail regardingthe vector unit 510 and the vector registers 514. Specifically, thevector unit 510 is a 6-wide vector processing unit (VPU) (see the16-wide ALU 528), which executes one or more of integer,single-precision float, and double-precision float instructions. The VPUsupports swizzling the register inputs with swizzle unit 520, numericconversion with numeric convert units 522A-B, and replication withreplication unit 524 on the memory input.

Processor with Integrated Memory Controller and Graphics

FIG. 6 is a block diagram of a processor 600 that may have more than onecore, may have an integrated memory controller, and may have integratedgraphics according to embodiments of the invention. The solid linedboxes in FIG. 6 illustrate a processor 600 with a single core 602A, asystem agent 610, a set of one or more bus controller units 616, whilethe optional addition of the dashed lined boxes illustrates analternative processor 600 with multiple cores 602A-N, a set of one ormore integrated memory controller unit(s) 614 in the system agent unit610, and special purpose logic 608.

Thus, different implementations of the processor 600 may include: 1) aCPU with the special purpose logic 608 being integrated graphics and/orscientific (throughput) logic (which may include one or more cores), andthe cores 602A-N being one or more general purpose cores (e.g., generalpurpose in-order cores, general purpose out-of-order cores, acombination of the two); 2) a coprocessor with the cores 602A-N being alarge number of special purpose cores intended primarily for graphicsand/or scientific (throughput); and 3) a coprocessor with the cores602A-N being a large number of general purpose in-order cores. Thus, theprocessor 600 may be a general-purpose processor, coprocessor orspecial-purpose processor, such as, for example, a network orcommunication processor, compression engine, graphics processor, GPGPU(general purpose graphics processing unit), a high-throughput manyintegrated core (MIC) coprocessor (including 30 or more cores), embeddedprocessor, or the like. The processor may be implemented on one or morechips. The processor 600 may be a part of and/or may be implemented onone or more substrates using any of a number of process technologies,such as, for example, BiCMOS, CMOS, or NMOS.

The memory hierarchy includes one or more levels of cache within thecores 602A-N, a set or one or more shared cache units 606, and externalmemory (not shown) coupled to the set of integrated memory controllerunits 614. The set of shared cache units 606 may include one or moremid-level caches, such as level 2 (L2), level 3 (L3), level 4 (L4), orother levels of cache, a last level cache (LLC), and/or combinationsthereof. While in one embodiment a ring based interconnect unit 612interconnects the special purpose logic 608, the set of shared cacheunits 606, and the system agent unit 610/integrated memory controllerunit(s) 614, alternative embodiments may use any number of well-knowntechniques for interconnecting such units. In one embodiment, coherencyis maintained between one or more cache units 606 and cores 602-A-N.

In some embodiments, one or more of the cores 602A-N are capable ofmulti-threading. The system agent 610 includes those componentscoordinating and operating cores 602A-N. The system agent unit 610 mayinclude for example a power control unit (PCU) and a display unit. ThePCU may be or include logic and components needed for regulating thepower state of the cores 602A-N and the special purpose logic 608. Thedisplay unit is for driving one or more externally connected displays.

The cores 602A-N may be homogenous or heterogeneous in terms ofarchitecture instruction set; that is, two or more of the cores 602A-Nmay be capable of executing the same instruction set, while others maybe capable of executing only a subset of that instruction set or adifferent instruction set.

Exemplary Computer Architectures

FIGS. 7-10 are block diagrams of exemplary computer architectures. Othersystem designs and configurations known in the arts for laptops,desktops, handheld PCs, personal digital assistants, engineeringworkstations, servers, network devices, network hubs, switches, embeddedprocessors, digital signal processors (DSPs), graphics devices, videogame devices, set-top boxes, micro controllers, cell phones, portablemedia players, hand held devices, and various other electronic devices,are also suitable. In general, a huge variety of systems or electronicdevices capable of incorporating a processor and/or other executionlogic as disclosed herein are generally suitable.

Referring now to FIG. 7 , shown is a block diagram of a system 700 inaccordance with one embodiment of the present invention. The system 700may include one or more processors 710, 715, which are coupled to acontroller hub 720. In one embodiment, the controller hub 720 includes agraphics memory controller hub (GMCH) 790 and an Input/Output Hub (IOH)750 (which may be on separate chips); the GMCH 790 includes memory andgraphics controllers to which are coupled memory 740 and a coprocessor745; the IOH 750 couples input/output (I/O) devices 760 to the GMCH 790.Alternatively, one or both of the memory and graphics controllers areintegrated within the processor (as described herein), the memory 740and the coprocessor 745 are coupled directly to the processor 710, andthe controller hub 720 in a single chip with the IOH 750.

The optional nature of additional processors 715 is denoted in FIG. 7with broken lines. Each processor 710, 715 may include one or more ofthe processing cores described herein and may be some version of theprocessor 600.

The memory 740 may be, for example, dynamic random access memory (DRAM),phase change memory (PCM), or a combination of the two. For at least oneembodiment, the controller hub 720 communicates with the processor(s)710, 715 via a multi-drop bus, such as a frontside bus (FSB),point-to-point interface, or similar connection 795.

In one embodiment, the coprocessor 745 is a special-purpose processor,such as, for example, a high-throughput MIC processor, a network orcommunication processor, compression engine, graphics processor, GPGPU,embedded processor, or the like. In one embodiment, controller hub 720may include an integrated graphics accelerator.

There can be a variety of differences between the processor 710, 715 interms of a spectrum of metrics of merit including architectural,microarchitectural, thermal, power consumption characteristics, and thelike.

In one embodiment, the processor 710 executes instructions that controldata processing operations of a general type. Embedded within theinstructions may be coprocessor instructions. The processor 710recognizes these coprocessor instructions as being of a type that shouldbe executed by the attached coprocessor 745. Accordingly, the processor710 issues these coprocessor instructions (or control signalsrepresenting coprocessor instructions) on a coprocessor bus or otherinterconnect, to coprocessor 745. Coprocessor(s) 745 accept and executethe received coprocessor instructions.

Referring now to FIG. 8 , shown is a block diagram of a first morespecific exemplary system 800 in accordance with an embodiment of thepresent invention. As shown in FIG. 8 , multiprocessor system 800 is apoint-to-point interconnect system, and includes a first processor 870and a second processor 880 coupled via a point-to-point interconnect850. Each of processors 870 and 880 may be some version of the processor600. In one embodiment of the invention, processors 870 and 880 arerespectively processors 710 and 715, while coprocessor 838 iscoprocessor 745. In another embodiment, processors 870 and 880 arerespectively processor 710 and coprocessor 745.

Processors 870 and 880 are shown including integrated memory controller(IMC) units 872 and 882, respectively. Processor 870 also includes aspart of its bus controller units point-to-point (P-P) interfaces 876 and878; similarly, second processor 880 includes P-P interfaces 886 and888. Processors 870, 880 may exchange information via a point-to-point(P-P) interface 850 using P-P interface circuits 878, 888. As shown inFIG. 8 , IMCs 872 and 882 couple the processors to respective memories,namely a memory 832 and a memory 834, which may be portions of mainmemory locally attached to the respective processors.

Processors 870, 880 may each exchange information with a chipset 890 viaindividual P-P interfaces 852, 854 using point to point interfacecircuits 876, 894, 886, 898. Chipset 890 may optionally exchangeinformation with the coprocessor 838 via a high-performance interface892. In one embodiment, the coprocessor 838 is a special-purposeprocessor, such as, for example, a high-throughput MIC processor, anetwork or communication processor, compression engine, graphicsprocessor, GPGPU, embedded processor, or the like.

A shared cache (not shown) may be included in either processor oroutside of both processors, yet connected with the processors via P-Pinterconnect, such that either or both processors' local cacheinformation may be stored in the shared cache if a processor is placedinto a low power mode.

Chipset 890 may be coupled to a first bus 816 via an interface 896. Inone embodiment, first bus 816 may be a Peripheral Component Interconnect(PCI) bus, or a bus such as a PCI Express bus or another I/Ointerconnect bus, although the scope of the present invention is not solimited.

As shown in FIG. 8 , various I/O devices 814 may be coupled to first bus816, along with a bus bridge 818 which couples first bus 816 to a secondbus 820. In one embodiment, one or more additional processor(s) 815,such as coprocessors, high-throughput MIC processors, GPGPU's,accelerators (such as, e.g., graphics accelerators or digital signalprocessing (DSP) units), field programmable gate arrays, or any otherprocessor, are coupled to first bus 816. In one embodiment, second bus820 may be a low pin count (LPC) bus. Various devices may be coupled toa second bus 820 including, for example, a keyboard and/or mouse 822,communication devices 827 and a storage unit 828 such as a disk drive orother mass storage device which may include instructions/code 830 anddata 840, in one embodiment. Further, an audio I/O 824 may be coupled tothe second bus 816. Note that other architectures are possible. Forexample, instead of the point-to-point architecture of FIG. 8 , a systemmay implement a multi-drop bus or other such architecture.

Referring now to FIG. 9 , shown is a block diagram of a second morespecific exemplary system 900 in accordance with an embodiment of thepresent invention. Like elements in FIGS. 8 and 9 bear like referencenumerals, and certain aspects of FIG. 8 have been omitted from FIG. 9 inorder to avoid obscuring other aspects of FIG. 9 .

FIG. 9 illustrates that the processors 870, 880 may include integratedmemory and I/O control logic (“CL”) 972 and 982, respectively. Thus, theCL 972, 982 include integrated memory controller units and include I/Ocontrol logic. FIG. 9 illustrates that not only are the memories 832,834 coupled to the CL 972, 982, but also that I/O devices 914 are alsocoupled to the control logic 972, 982. Legacy I/O devices 915 arecoupled to the chipset 890.

Referring now to FIG. 10 , shown is a block diagram of a SoC 1000 inaccordance with an embodiment of the present invention. Similar elementsin FIG. 6 bear like reference numerals. Also, dashed lined boxes areoptional features on more advanced SoCs. In FIG. 10 , an interconnectunit(s) 1002 is coupled to: an application processor 1010 which includesa set of one or more cores 602A-N, cache units 604A-N, and shared cacheunit(s) 606; a system agent unit 610; a bus controller unit(s) 616; anintegrated memory controller unit(s) 614; a set or one or morecoprocessors 1020 which may include integrated graphics logic, an imageprocessor, an audio processor, and a video processor; a static randomaccess memory (SRAM) unit 1030; a direct memory access (DMA) unit 1032;and a display unit 1040 for coupling to one or more external displays.In one embodiment, the coprocessor(s) 1020 include a special-purposeprocessor, such as, for example, a network or communication processor,compression engine, GPGPU, a high-throughput MIC processor, embeddedprocessor, or the like.

Embodiments of the mechanisms disclosed herein may be implemented inhardware, software, firmware, or a combination of such implementationapproaches. Embodiments of the invention may be implemented as computerprograms or program code executing on programmable systems comprising atleast one processor, a storage system (including volatile andnon-volatile memory and/or storage elements), at least one input device,and at least one output device.

Program code, such as code 830 illustrated in FIG. 8 , may be applied toinput instructions to perform the functions described herein andgenerate output information. The output information may be applied toone or more output devices, in known fashion. For purposes of thisapplication, a processing system includes any system that has aprocessor, such as, for example; a digital signal processor (DSP), amicrocontroller, an application specific integrated circuit (ASIC), or amicroprocessor.

The program code may be implemented in a high level procedural or objectoriented programming language to communicate with a processing system.The program code may also be implemented in assembly or machinelanguage, if desired. In fact, the mechanisms described herein are notlimited in scope to any particular programming language. In any case,the language may be a compiled or interpreted language.

One or more aspects of at least one embodiment may be implemented byrepresentative instructions stored on a machine-readable medium whichrepresents various logic within the processor, which when read by amachine causes the machine to fabricate logic to perform the techniquesdescribed herein. Such representations, known as “IP cores” may bestored on a tangible, machine readable medium and supplied to variouscustomers or manufacturing facilities to load into the fabricationmachines that actually make the logic or processor.

Such machine-readable storage media may include, without limitation,non-transitory, tangible arrangements of articles manufactured or formedby a machine or device, including storage media such as hard disks, anyother type of disk including floppy disks, optical disks, compact diskread-only memories (CD-ROMs), compact disk rewritables (CD-RWs), andmagneto-optical disks, semiconductor devices such as read-only memories(ROMs), random access memories (RAMs) such as dynamic random accessmemories (DRAMs), static random access memories (SRAMs), erasableprogrammable read-only memories (EPROMs), flash memories, electricallyerasable programmable read-only memories (EEPROMs), phase change memory(PCM), magnetic or optical cards, or any other type of media suitablefor storing electronic instructions.

Accordingly, embodiments of the invention also include non-transitory,tangible machine-readable media containing instructions or containingdesign data, such as Hardware Description Language (HDL), which definesstructures, circuits, apparatuses, processors and/or system featuresdescribed herein. Such embodiments may also be referred to as programproducts.

Emulation (Including Binary Translation, Code Morphing, Etc.)

In some cases, an instruction converter may be used to convert aninstruction from a source instruction set to a target instruction set.For example, the instruction converter may translate (e.g., using staticbinary translation, dynamic binary translation including dynamiccompilation), morph, emulate, or otherwise convert an instruction to oneor more other instructions to be processed by the core. The instructionconverter may be implemented in software, hardware, firmware, or acombination thereof. The instruction converter may be on processor, offprocessor, or part on and part off processor.

FIG. 11 is a block diagram contrasting the use of a software instructionconverter to convert binary instructions in a source instruction set tobinary instructions in a target instruction set according to embodimentsof the invention. In the illustrated embodiment, the instructionconverter is a software instruction converter, although alternativelythe instruction converter may be implemented in software, firmware,hardware, or various combinations thereof. FIG. 11 shows a program in ahigh level language 1102 may be compiled using a first compiler 1104 togenerate a first binary code (e.g., x86) 1106 that may be nativelyexecuted by a processor with at least one first instruction set core1116. In some embodiments, the processor with at least one firstinstruction set core 1116 represents any processor that can performsubstantially the same functions as an Intel processor with at least onex86 instruction set core by compatibly executing or otherwise processing(1) a substantial portion of the instruction set of the Intel x86instruction set core or (2) object code versions of applications orother software targeted to run on an Intel processor with at least onex86 instruction set core, in order to achieve substantially the sameresult as an Intel processor with at least one x86 instruction set core.The first compiler 1104 represents a compiler that is operable togenerate binary code of the first instruction set 1106 (e.g., objectcode) that can, with or without additional linkage processing, beexecuted on the processor with at least one first instruction set core1116. Similarly, FIG. 11 shows the program in the high level language1102 may be compiled using an alternative instruction set compiler 1108to generate alternative instruction set binary code 1110 that may benatively executed by a processor without at least one first instructionset core 1114 (e.g., a processor with cores that execute the MIPSinstruction set of MIPS Technologies of Sunnyvale, Calif. and/or thatexecute the ARM instruction set of ARM Holdings of Sunnyvale, Calif.).The instruction converter 1112 is used to convert the first binary code1106 into code that may be natively executed by the processor without anfirst instruction set core 1114. This converted code is not likely to bethe same as the alternative instruction set binary code 1110 because aninstruction converter capable of this is difficult to make; however, theconverted code will accomplish the general operation and be made up ofinstructions from the alternative instruction set. Thus, the instructionconverter 1112 represents software, firmware, hardware, or a combinationthereof that, through emulation, simulation or any other process, allowsa processor or other electronic device that does not have a firstinstruction set processor or core to execute the first binary code 1106.

Apparatus and Method for Digital Signal Processing Instructions

Digital signal processing (DSP) instructions are described below. In oneembodiment, the circuitry and logic to perform the DSP operations isintegrated within the execution engine unit 450 shown in FIG. 4B, withinthe various cores described above (see, e.g., cores 602A-N in FIGS. 6and 10 ), and/or within the vector unit 510 shown in FIG. 5A. Forexample, the various source and destination registers may be SIMDregisters within the physical register file unit(s) 458 in FIG. 4Band/or vector registers 310 in FIG. 3 . The multiplication circuits,adder circuits, accumulation circuits, and other circuitry describedbelow may be integrated within the execution components of thearchitectures described above including, by way of example and notlimitation, the execution unit(s) 462 in FIG. 4B. It should be noted,however, that the underlying principles of the invention are not limitedto these specific architectures.

One embodiment of the invention includes circuitry and/or logic forprocessing digital signal processing (DSP) instructions. In particular,one embodiment comprises a multiply-accumulate (MAC) architecture witheight 16×16-bit multipliers and two 64-bit accumulators. The instructionset architecture (ISA) described below can process various multiply andMAC operations on 128-bit packed (8-bit, 16-bit or 32-bit data elements)integer, fixed point and complex data types. In addition, certaininstructions have direct support for highly efficient Fast FourierTransform (FFT) and Finite Impulse Response (FIR) filtering, andpost-processing of accumulated data by shift, round, and saturateoperations.

One embodiment of the new DSP instructions use a VEX.128 prefix basedopcode encoding and several of the SSE/SSE2/AVX instructions that handlepost-processing of data are used with the DSP ISA. The VEX-encoded128-bit DSP instructions with memory operands may have relaxed memoryalignment requirements.

In one embodiment, the instructions also support a variety of integerand fixed point data types including:

-   -   1) a Q31 data type for signals requiring analog to digital        conversion (ADC) and digital to analog conversion (DAC) with        greater than 16 bits;    -   2) a Q15 data type which is common in DSP algorithms;    -   3) a complex 16-bit data type; and    -   4) a complex 32-bit data type.

The instruction set architecture described herein targets a wide rangeof standard DSP (e.g., FFT, filtering, pattern matching, correlation,polynomial evaluation, etc) and statistical operations (e.g., mean,moving average, variance, etc.).

Target applications of the embodiments of the invention include sensor,audio, classification tasks for computer vision, and speech recognition.The DSP ISA described herein includes a wide range of instructions thatare applicable to deep neural networks (DNN), automatic speechrecognition (ASR), sensor fusion with Kalman filtering, other major DSPapplications, etc. Given the sequence of weights {w₁, w₂, . . . w_(k)}and the input sequence {x₁, x₂, x₃, . . . , x_(n)} many imageprocessing, machine learning tasks require to compute the resultsequence {y₁, y₂, y₃, . . . y_(n+1−k)} defined byy_(i)=w₁x_(i)+w₂x_(i+1)+ . . . +w_(k)x_(i+k−1).

FIG. 12 illustrates an exemplary processor 1255 on which embodiments ofthe invention may be implemented which includes a plurality of cores 0-Nfor simultaneously executing a plurality of instruction threads. Theillustrated embodiment includes DSP instruction decode circuitry/logic1231 within the decoder 1230 and DSP instruction executioncircuitry/logic 1341 within the execution unit 1240. These pipelinecomponents may perform the operations described herein responsive to thedecoding and execution of the DSP instructions. While details of only asingle core (Core 0) are shown in FIG. 12 , it will be understood thateach of the other cores of processor 1255 may include similarcomponents.

Prior to describing specific details of the embodiments of theinvention, a description of the various components of the exemplaryprocessor 1255 are provided directly below. The plurality of cores 0-Nmay each include a memory management unit 1290 for performing memoryoperations (e.g., such as load/store operations), a set of generalpurpose registers (GPRs) 1205, a set of vector registers 1206, and a setof mask registers 1207. In one embodiment, multiple vector data elementsare packed into each vector register 1206 which may have a 512-bit widthfor storing two 256-bit values, four 128-bit values, eight 64-bitvalues, sixteen 32-bit values, etc. However, the underlying principlesof the invention are not limited to any particular size/type of vectordata. In one embodiment, the mask registers 1207 include eight 64-bitoperand mask registers used for performing bit masking operations on thevalues stored in the vector registers 1206 (e.g., implemented as maskregisters k0-k7 described herein). However, the underlying principles ofthe invention are not limited to any particular mask register size/type.

Each core 0-N may include a dedicated Level 1 (L1) cache 1212 and Level2 (L2) cache 1211 for caching instructions and data according to aspecified cache management policy. The L1 cache 1212 includes a separateinstruction cache 1220 for storing instructions and a separate datacache 1221 for storing data. The instructions and data stored within thevarious processor caches are managed at the granularity of cache lineswhich may be a fixed size (e.g., 64, 128, 512 Bytes in length). Eachcore of this exemplary embodiment has an instruction fetch unit 1210 forfetching instructions from main memory 1200 and/or a shared Level 3 (L3)cache 1216. The instruction fetch unit 1210 includes various well knowncomponents including a next instruction pointer 1203 for storing theaddress of the next instruction to be fetched from memory 1200 (or oneof the caches); an instruction translation look-aside buffer (ITLB) 1204for storing a map of recently used virtual-to-physical instructionaddresses to improve the speed of address translation; a branchprediction unit 1202 for speculatively predicting instruction branchaddresses; and branch target buffers (BTBs) 1201 for storing branchaddresses and target addresses.

As mentioned, a decode unit 1230 includes DSP instruction decodecircuitry/logic 1231 for decoding the DSP instructions described hereininto micro-operations or “uops” and the execution unit 1240 includes DSPinstruction execution circuitry/logic 1241 for executing the DSPinstructions. A writeback/retirement unit 1250 retires the executedinstructions and writes back the results.

Vector Packed Dual Complex by Complex Conjugate Multiply Add andAccumulate of Imaginary Part

One embodiment of the invention uses the architecture shown in FIG. 14Ato perform dual complex-by-complex conjugate multiply add and accumulateusing packed real and imaginary data elements. The described embodimentsperform operations on signed words in 128-bit packed data registers. Forexample, one embodiment stores packed data values in xmm2, and xmm3/m128where xmm2 stores complex conjugates and xmm3/m128 stores complexnumbers.

In one embodiment, a first accumulator performs the operation: Imaginary((16+16i)×(16−16i))+Imaginary ((16+16i)×(16−16i))+64i=64i to calculateand accumulate a first imaginary component and a second accumulatorperforms the operation: Imaginary ((16+16i)×(16−16i))+Imaginary((16+16i)×(16−16i))+64i=64i to calculate and accumulate a secondimaginary component (e.g., such as xmm1, xmm2 and xmm3/m128). It shouldbe noted, however, that the underlying principles of the invention arenot so limited. In the foregoing notation, the numbers represent thenumber of bits used to represent real and imaginary components of eachcomplex number (e.g., 16+16i means a complex number represented by a 16bit real component and a 16 bit imaginary component).

One particular embodiment decodes and executes a single instruction toperform a dual complex-by-complex conjugate multiply add and accumulateusing packed real and imaginary data elements, identified herein withthe mnemonic VPCCDPWQIMM. The following code specifies the individualoperations performed in one embodiment, where TEMP0 and TEMP1 areregisters or memory locations for storing intermediate values and DESTis a destination register:

-   -   TEMP0[33:0]←(((SRC2[47:32]*SRC3        [63:48])−(SRC2[63:48]*SRC3[47:32]))+((SRC2[15:0]*SRC3[31:16])−(SRC2[31:16]*SRC3[15:0])));    -   TEMP1[33:0]←(((SRC2[111:96]*SRC3[127:112])−(SRC2[127:112]*SRC3[111:96]))+((SRC2[79:64]*SRC3[95:80])−(SRC2[95:80]*SRC3[79:64])));    -   DEST[63:0]←AddToQuadword({{30{TEMP0[33]}}, TEMP0[33:0]},        DEST[63:0]);    -   DEST[127:64]←AddToQuadword({{30{TEMP1[33]}}, TEMP1[33:0]},        DEST[127:64]);

Thus, TEMP0 stores results of the above multiplications, additions, andsubtractions using data elements from the lower half of SRC2 and SRC3(i.e., bits 63:0) and TEMP1 stores results of the multiplications,additions, and subtractions using data elements from the upper half ofSRC2 and SRC3 (i.e., bits 127:64). Imaginary numbers are generated bythese operations because each product comprises an imaginary numbermultiplied by a real number.

The results in TEMP0 are then accumulated with the existing quadword inthe lower 64 bits of DEST (i.e., 63:0) and the results in TEMP1 areaccumulated with the existing quadword in the upper 64 bits of DEST(i.e., 127:64). In one embodiment, the results in TEMP0 and TEMP1 aresign-extended or zero-extended to an appropriate size for accumulatingthe results with the values from the destination register (e.g., 64bits). In the particular example shown in the code above, the resultsare sign-extended. Regardless of the type of extension performed, thefinal result comprises accumulated imaginary number components.

Returning to FIG. 14A, the first source register SRC2 1401 stores dataelements S2A-S2H and the second source register SRC3 1402 stores dataelements S3A-S3H (S2 is used here as shorthand for SRC2 and S3 forSRC3). In one embodiment, elements A, C, E, and G are real and dataelements B, D, F, and H are imaginary. Eight multipliers 1405 multiplyeach real data element in SRC2 with an imaginary data element in SRC3and multiply each imaginary data element in SRC2 with a real dataelement in SRC3 to generate 8 imaginary products. In this embodiment,the products added/subtracted and stored in TEMP0 areS2C*S3D−S2D*S3C+S2A*S3B−S2B*S3A and the products added/subtracted andstored in TEMP1 are S2G*S3H−S2H*S3G+S2E*S3F−S2F*S3E. First and secondsets of adder networks 1410-1411 add and subtract the various imaginaryproducts according to the above code. For example, adder network 1410performs the addition and subtraction operations:

-   -   S2C*S3D−S2D*S3C+S2A*S3B−S2B*S3A;        and adder network 1411 performs the addition operation:    -   S2G*S3H−S2H*S3G+S2E*S3F−S2F*S3E.

The results from adder network 1410 are stored in TEMP0 and the resultsfrom adder network 1411 are stored in TEMP1. In one embodiment, prior toaccumulation, these results are sign-extended or zero-extended to anappropriate size for accumulating the results with the values from thedestination register (e.g., 64 bits). In the particular example shown inthe code above, the results are sign-extended.

Accumulation circuitry comprising adders 1420-1421 adds the aboveresults with previously-accumulated results (if any) stored in theSRC1/DEST register 1460. In particular, the results generated by addernetwork 1410 (after being extended) are added to the accumulated datastored in element locations A-D (i.e., the lower 64 bits) of theSRC1/DEST register 1460. The imaginary results are saturated bysaturation circuitry 1440 (i.e., if one or more of the values are largerthan the maximum supported value then the maximum value is output). Theaccumulated results are then stored back in the SRC1/DEST register 1460to element locations A-D (the lower 64 bits). Similarly, the outputs ofadder network 1411 (after being extended) are added to the accumulateddata stored in element locations E-H (the upper 64 bits) in theSRC1/DEST register 1460. The accumulated imaginary results are saturatedby saturation circuitry 1441 (if necessary) and stored back to dataelement locations E-H (the upper 64 bits) of the SRC1/DEST register1460.

A method in accordance with one embodiment is illustrated in FIG. 15 .The method may be implemented within the context of the processorarchitectures described herein, but is not limited to any particularprocessor architecture.

At 1501 a first instruction is fetched having fields for an opcode andfirst and second packed data source operands representing complexnumbers having real and imaginary values and a packed data destinationoperand. At 1502 the first instruction is decoded. At 1503, the real andimaginary values associated with the first and second source operandsare stored as packed data elements in the first and second sourceregisters and the first instruction is scheduled for execution. Asmentioned, in one embodiment, the first and second source operands arestored in 128-bit packed data registers storing 16-bit packed dataelements, with each packed data element comprising a real or animaginary value.

At 1504 the first decoded instruction is executed to multiply selectedreal values from the first operand with selected imaginary values fromthe second operand to generate first imaginary products and to multiplyselected imaginary values from the first operand with selected realvalues from the second operand to generate second imaginary products.

At 1505, selected combinations of the first and second imaginaryproducts are added and subtracted to generate first and second temporaryresults, respectively. As described above, in one embodiment, thiscomprises the operations: S2C*S3D−S2D*S3C+S2A*S3B−S2B*S3A andS2G*S3H−S2H*S3G+S2E*S3F−S2F*S3E, where S2C*S3D, S2D*S3C, S2A*S3B, andS2B*S3A are the first set of imaginary products and S2G*S3H, S2H*S3G,S2E*S3F, and S2F*S3E are the second set of imaginary products.

In one embodiment, at 1505, the first temporary results arezero-extended or sign-extended and combined with the lower 64-bit packeddata element from the destination register (covering 16-bit dataelements A-D) and the accumulated results are stored back to the lowerfour packed data element locations in the destination register.Similarly, the second temporary results are combined with the upper64-bit packed data element from the destination register (covering16-bit data elements E-H) and the accumulated results are stored back tothe upper 64 bits in the destination register. In one embodiment, theaccumulated results are saturated if necessary prior to being storedback to the destination register.

At 1506, the results of the first instruction are committed to memory(e.g., and made globally visible).

While the real and imaginary values described above are 16 bits inlength, the underlying principles of the invention may be implementedusing data elements of any size. For example, the real and imaginarycomponents may be 8 bits, 32 bits, or 64 bits while still complying withthe underlying principles of the invention.

Vector Packed Dual Complex by Complex Conjugate Multiply and Add, NegateSum and Accumulate of Imaginary Part

One embodiment of the invention uses the architecture shown in FIG. 14Ato perform dual complex by complex conjugate multiply and add, negatethe sum and accumulate the imaginary component using packed real andimaginary values. As described below, one embodiment also performs two'scomplement negation by inverting the bits of temporary results andadding 1 and may also sign-extend or zero-extend the results prior toaccumulation. The described embodiments perform operations on signedwords in 128-bit packed data registers. For example, one embodimentstores packed data values in xmm2, and xmm3/m128 where xmm2 storescomplex conjugates and xmm3/m128 stores complex numbers.

In one embodiment, a first accumulator performs the operation:Imaginary−((16+16i)×(16−16i))+Imaginary ((16+16i)×(16−16i))+64i=64i tocalculate and accumulate a first imaginary component and a secondaccumulator performs the operation:Imaginary−((16+16i)×(16−16i))+Imaginary ((16+16i)×(16−16i))+64i=64i tocalculate and accumulate a second imaginary component (e.g., such asxmm1, xmm2 and xmm3/m128). It should be noted, however, that theunderlying principles of the invention are not so limited. As mentioned,in the foregoing notation, the numbers represent the number of bits usedto represent each number (e.g., 16+16i means a complex numberrepresented by a 16-bit real component and a 16-bit imaginarycomponent).

One particular embodiment decodes and executes a single instruction toperform a dual complex-by-complex conjugate multiply add, negate sum,and accumulate using packed real and imaginary data elements, identifiedherein with the mnemonic VPNCCDPWQIMM. The following code specifies theindividual operations performed in one embodiment, where TEMP0, TEMP1,TEMP2, and TEMP3 are registers or memory locations for storingintermediate values and DEST is a destination register:

-   -   TEMP0[33:0]←(((SRC2[47:32]*SRC3[63:48])−(SRC2[63:48]*SRC3[47:32]))+((SRC2[15:0]*SRC3[31:16])−(SRC2[31:16]*SRC3[15:0])));    -   TEMP1[33:0]←(((SRC2[111:96]*SRC3[127:112])−(SRC2[127:112]*SRC3[111:96]))+((SRC2[79:64]*SRC3[95:80])−(SRC2[95:80]*SRC3[79:64])));    -   TEMP2[33:0]←(˜TEMP0[33:0]+1′b1);    -   TEMP3[33:0]←(˜TEMP1[33:0]+1′b1); (* two's complement negation*)    -   DEST[63:0]←AddToQuadword({{30{TEMP2[33]}}, TEMP2[33:0]},        DEST[63:0]);    -   DEST[127:64]←AddToQuadword({{30{TEMP3[33]}}, TEMP3[33:0]},        DEST[127:64]);

Thus, TEMP0 stores results of the above multiplications, additions, andsubtractions using data elements from the lower half of SRC2 and SRC3(i.e., bits 63:0) and TEMP1 stores results of the multiplications,additions, and subtractions using data elements from the upper half ofSRC2 and SRC3 (i.e., bits 127:64). Imaginary numbers are generated bythese operations because each product comprises an imaginary numbermultiplied by a real number.

In one embodiment, in accordance with properties of two's complementnegation, the results stored in TEMP0 and TEMP1 are each inverted and abinary 1 is added to the inverted values to negate the temporaryresults. The negated results are then stored in TEMP2 and TEMP3.

The negated results in TEMP2 are then accumulated with the existingquadword in the lower 64 bits of DEST (i.e., 63:0) and the results inTEMP3 are accumulated with the existing quadword in the upper 64 bits ofDEST (i.e., 127:64). Thus, the final result comprises a plurality ofaccumulated imaginary number components.

Returning to FIG. 14A, the first source register SRC2 1401 stores dataelements S2A-S2H and the second source register SRC3 1402 stores dataelements S3A-S3H (S2 is used here as an abbreviation for SRC2 and S3 isSRC3). In one embodiment, elements A, C, E, and G are real and dataelements B, D, F, and H are imaginary. Eight multipliers 1405 multiplyeach real data element in SRC2 with an imaginary data element in SRC3and multiply each imaginary data element in SRC2 with a real dataelement in SRC3 to generate 8 imaginary products. In this embodiment,the products added/subtracted and stored in TEMP0 areS2C*S3D−S2D*S3C+S2A*S3B−S2B*S3A and the products added/subtracted andstored in TEMP1 are S2G*S3H−S2H*S3G+S2E*S3F−S2F*S3E. First and secondsets of adder networks 1410-1411 add and subtract the various imaginaryproducts according to the above code. For example, adder network 1410performs the addition and subtraction operations:

-   -   S2C*S3D−S2D*S3C+S2A*S3B−S2B*S3A;        and adder network 1411 performs the addition operation:    -   S2G*S3H−S2H*S3G+S2E*S3F−S2F*S3E.

Either the adder networks 1410-1411 or other circuitry/logic (not shown)inverts the above temporary results and adds a binary 1 to the invertedresults to generate final temporary results which are stored in TEMP2and TEMP3. As mentioned above, this operation is referred to as two'scomplement negation which is used to negate the temporary results.

Accumulation circuitry comprising adders 1420-1421 adds the aboveresults with previously-accumulated results (if any) stored in theSRC1/DEST register 1460. In particular, the outputs of adder network1410, AN0_A to AN0_D, are added to the accumulated data elements A-D,respectively, in the SRC1/DEST register 1460. The imaginary results aresaturated by saturation circuitry 1440 (i.e., if one or more of thevalues are larger than the maximum supported value then the maximumvalue is output). The results are then stored back in destination dataelements A-D. Similarly, the outputs of adder network 1411, AN1_A toAN1_D, are added to the accumulated data elements E-H, respectively, inthe SRC1/DEST register 1460. The imaginary results are saturated bysaturation circuitry 1441 and output back to destination data elementsE-H.

FIG. 14B illustrates additional details of one embodiment includingtwo's complement negation circuitry 1470 and 1471 which uses two'scomplement negation to negate the product sums calculated by the addernetworks 1410 and 1411, respectively. Extend circuitry 1480 and 1481receives the negated product sums and responsively zero-extends orsign-extends these values to generate a result of an appropriate size toaccumulate with the current SRC1/DEST 1460 register values (e.g., 64bits). Zero extending in one embodiment comprises adding a plurality ofzeroes to the values while sign-extending comprises replicating a bitvalue. Accumulators 1490-1491 then perform the accumulation operationsdescribed herein using the 64-bit temporary results and the packed64-bit values from the SRC1/DEST register 1460.

A method in accordance with one embodiment is illustrated in FIG. 16 .The method may be implemented within the context of the processorarchitectures described herein, but is not limited to any particularprocessor architecture.

At 1601 a first instruction is fetched having fields for an opcode andfirst and second packed data source operands representing complexnumbers having real and imaginary values and a packed data destinationoperand. At 1602 the first instruction is decoded. At 1603, the real andimaginary values associated with the first and second source operandsare stored as packed data elements in the first and second sourceregisters and the first instruction is scheduled for execution. Asmentioned, in one embodiment, the first and second source operands arestored in 128-bit packed data registers storing 16-bit packed dataelements, with each packed data element comprising a real or animaginary value.

At 1604 the first decoded instruction is executed to multiply selectedreal values from the first operand with selected imaginary values fromthe second operand to generate first imaginary products and to multiplyselected imaginary values from the first operand with selected realvalues from the second operand to generate second imaginary products.

At 1605, selected combinations of the first and second imaginaryproducts are added and subtracted to generate first and second sets oftemporary results, respectively. As described above, in one embodiment,this comprises the operations: S2C*S3D−S2D*S3C+S2A*S3B−S2B*S3A andS2G*S3H−S2H*S3G+S2E*S3F−S2F*S3E, where S2C*S3D, S2D*S3C, S2A*S3B, andS2B*S3A are the first set of imaginary products and S2G*S3H, S2H*S3G,S2E*S3F, and S2F*S3E are the second set of imaginary products.

At 1606, the bits of the first and second temporary results are invertedand 1 is added to each to generate third and fourth temporary results,respectively. As mentioned, this may be done using third and fourthstorage locations (e.g., TEMP2 and TEMP3).

In one embodiment, at 1607, after the third and fourth temporary resultsare sign-extended (or zero-extended) the third temporary results arecombined with the packed 64-bit data element in the lower 64 bits of thedestination register (16-bit elements A-D) and the accumulated resultsstored back to the lower 64 bits of the destination register. Similarly,the fourth temporary results are combined with the packed 64-bit dataelement in the upper 64 bits of the destination register (16-bitelements E-H) and the accumulated results are stored back to the upper64 bits in the destination register. In one embodiment, the accumulatedresults are saturated if necessary prior to being stored back to thedestination register.

At 1608, the results of the first instruction are committed to memory(e.g., and made globally visible).

While the real and imaginary values described above are 16 bits inlength, the underlying principles of the invention may be implementedusing data elements of any size. For example, the real and imaginarycomponents may be 8 bits, 32 bits, or 64 bits while still complying withthe underlying principles of the invention.

In the foregoing specification, the embodiments of invention have beendescribed with reference to specific exemplary embodiments thereof. Itwill, however, be evident that various modifications and changes may bemade thereto without departing from the broader spirit and scope of theinvention as set forth in the appended claims. The specification anddrawings are, accordingly, to be regarded in an illustrative rather thana restrictive sense.

Embodiments of the invention may include various steps, which have beendescribed above. The steps may be embodied in machine-executableinstructions which may be used to cause a general-purpose orspecial-purpose processor to perform the steps. Alternatively, thesesteps may be performed by specific hardware components that containhardwired logic for performing the steps, or by any combination ofprogrammed computer components and custom hardware components.

As described herein, instructions may refer to specific configurationsof hardware such as application specific integrated circuits (ASICs)configured to perform certain operations or having a predeterminedfunctionality or software instructions stored in memory embodied in anon-transitory computer readable medium. Thus, the techniques shown inthe Figures can be implemented using code and data stored and executedon one or more electronic devices (e.g., an end station, a networkelement, etc.). Such electronic devices store and communicate(internally and/or with other electronic devices over a network) codeand data using computer machine-readable media, such as non-transitorycomputer machine-readable storage media (e.g., magnetic disks; opticaldisks; random access memory; read only memory; flash memory devices;phase-change memory) and transitory computer machine-readablecommunication media (e.g., electrical, optical, acoustical or other formof propagated signals—such as carrier waves, infrared signals, digitalsignals, etc.). In addition, such electronic devices typically include aset of one or more processors coupled to one or more other components,such as one or more storage devices (non-transitory machine-readablestorage media), user input/output devices (e.g., a keyboard, atouchscreen, and/or a display), and network connections. The coupling ofthe set of processors and other components is typically through one ormore busses and bridges (also termed as bus controllers). The storagedevice and signals carrying the network traffic respectively representone or more machine-readable storage media and machine-readablecommunication media. Thus, the storage device of a given electronicdevice typically stores code and/or data for execution on the set of oneor more processors of that electronic device. Of course, one or moreparts of an embodiment of the invention may be implemented usingdifferent combinations of software, firmware, and/or hardware.Throughout this detailed description, for the purposes of explanation,numerous specific details were set forth in order to provide a thoroughunderstanding of the present invention. It will be apparent, however, toone skilled in the art that the invention may be practiced without someof these specific details. In certain instances, well known structuresand functions were not described in elaborate detail in order to avoidobscuring the subject matter of the present invention. Accordingly, thescope and spirit of the invention should be judged in terms of theclaims which follow.

What is claimed is:
 1. A processor comprising: a hardware decoder todecode a first instruction to generate a decoded instruction; a firstsource register to store a first plurality of packed real and imaginarydata elements comprising a first plurality of complex numbers; a secondsource register to store a second plurality of packed real and imaginarydata elements comprising a second plurality of complex numbers, whereineach of the second plurality of complex numbers comprises a complexconjugate of a corresponding complex number of the first plurality ofcomplex numbers; and execution circuitry to execute the decodedinstruction, the execution circuitry comprising: at least one hardwaremultiplier to multiply selected real and imaginary data elements in thefirst source register and the second source register, wherein the atleast one hardware multiplier is to multiply each selected imaginarydata element in the first source register with a selected real dataelement in the second source register and to multiply each selected realdata element in the first source register with a selected imaginary dataelement in the second source register to generate a plurality ofimaginary products; at least one hardware adder to add a first subset ofthe plurality of imaginary products and subtract a second subset of theplurality of imaginary products to generate a first temporary result andto add a third subset of the plurality of imaginary products andsubtract a fourth subset of the plurality of imaginary products togenerate a second temporary result; and accumulation circuitry tocombine the first temporary result with first data from a destinationregister to generate a first final result and to combine the secondtemporary result with second data from the destination register togenerate a second final result and to store the first final result andthe second final result back in the destination register.
 2. Theprocessor of claim 1, wherein the first and second plurality of packedreal and imaginary data elements are stored as 16-bit data elements inthe first and second source registers, each imaginary data element beingstored in a data element location adjacent to a data element location ofits corresponding real data element, each combination of a real andimaginary data element representing a complex number.
 3. The processorof claim 2, wherein the first and second source registers comprise128-bit packed data registers configurable with data element positionsA, B, C, D, E, F, G, and H storing data elements A, B, C, D, E, F, G,and H, respectively, and wherein data elements A, C, E, and G are realdata elements and data elements B, D, F, and H are correspondingimaginary data elements.
 4. The processor of claim 3, wherein to executethe decoded instruction, the at least one hardware multiplier is toperform multiplications of S1C*S2D, S1D*S2C, S1A*S2B, S1B*S2A, S1G*S2H,S1H*S2G, S1E*S2F, S1F*S2E to generate the plurality of imaginaryproducts, where S1 identifies the first source register, S2 identifiesthe second source register and A-H identify the packed data elements indata element positions A-H in the first and second source registers,respectively.
 5. The processor of claim 4, wherein adding andsubtracting the first and second subsets of the plurality of imaginaryproducts, respectively, comprises S1C*S2D−S1D*S2C+S1A*S2B−S1B*S2A andadding and subtracting of the third and fourth subsets of the pluralityof imaginary products, respectively, comprisesS1G*S2H−S1H*S2G+S1E*S2F−S1F*S2E to generate the first temporary resultand second temporary result, respectively.
 6. The processor of claim 5,further comprising: extension circuitry to zero-extend or sign-extendthe first and second temporary results to 64-bit values prior toaccumulation with the first and second data from the destinationregister, respectively.
 7. The processor of claim 6, wherein theextension circuitry is to add zeroes to the first and second temporaryresults to convert the first and second temporary results to 64-bitvalues.
 8. The processor of claim 6, wherein a value in a mostsignificant bit position of the first temporary result and secondtemporary result is repeated a number of times to convert the firsttemporary result and second temporary result to 64-bit values.
 9. Amethod comprising: decoding a first instruction to generate a decodedinstruction; storing a first plurality of packed real and imaginary dataelements in a first source register, the first plurality of packed realand imaginary data elements comprising a first plurality of complexnumbers; storing a second plurality of packed real and imaginary dataelements in a second source register, the second plurality of packedreal and imaginary data elements comprising a second plurality ofcomplex numbers, wherein each of the second plurality of complex numberscomprises a complex conjugate of a corresponding complex number of thefirst plurality of complex numbers; multiplying selected real andimaginary data elements in the first source register and the secondsource register including multiplying each selected imaginary dataelement in the first source register with a selected real data elementin the second source register and multiplying each selected real dataelement in the first source register with a selected imaginary dataelement in the second source register to generate a plurality ofimaginary products; adding a first subset of the plurality of imaginaryproducts and subtracting a second subset of the plurality of imaginaryproducts to generate a first temporary result and adding a third subsetof the plurality of imaginary products and subtracting a fourth subsetof the plurality of imaginary products to generate a second temporaryresult; accumulating the first temporary result with first data from adestination register to generate a first final result and accumulatingthe second temporary result with second data from the destinationregister to generate a second final result; and storing the first finalresult and the second final result back in the destination register. 10.The method of claim 9, wherein the first and second plurality of packedreal and imaginary data elements are stored as 16-bit data elements inthe first and second source registers, each imaginary data element beingstored in a data element location adjacent to a data element location ofits corresponding real data element, each combination of a real andimaginary data element representing a complex number.
 11. The method ofclaim 10, wherein the first and second source registers comprise 128-bitpacked data registers configurable with data element positions A, B, C,D, E, F, G, and H storing data elements A, B, C, D, E, F, G, and H,respectively, and wherein data elements A, C, E, and G are real dataelements and data elements B, D, F, and H are corresponding imaginarydata elements.
 12. The method of claim 11, wherein multiplying eachselected imaginary data element in the first source register with aselected real data element in the second source register and multiplyingeach selected real data element in the first source register with aselected imaginary data element in the second source register togenerate a plurality of imaginary products further comprise: multiplyingS1C*S2D, S1D*S2C, S1A*S2B, S1B*S2A, S1G*S2H, S1H*S2G, S1E*S2F, S1F*S2Eto generate the plurality of imaginary products, where S1 identifies thefirst source register, S2 identifies the second source register and A-Hidentify the packed data elements in data element positions A-H in thefirst and second source registers, respectively.
 13. The method of claim12, wherein adding of the first subset of the plurality of imaginaryproducts and subtracting of the second subset of the plurality ofimaginary products comprise S1C*S2D−S1D*S2C+S1A*S2B−S1B*S2A and addingof the third subset of the plurality of imaginary products andsubtracting of the fourth subset of the plurality of imaginary productscomprise S1G*S2H−S1H*S2G+S1E*S2F−S1F*S2E to generate the first temporaryresult and second temporary result, respectively.
 14. The method ofclaim 13, further comprising: zero-extending or sign-extending the firstand second temporary results to 64-bit values prior to accumulation withthe first and second data from the destination register, respectively.15. The method of claim 14, wherein zeroes are added to the first andsecond temporary results to convert the first and second temporaryresults to 64-bit values.
 16. The method of claim 14, wherein a value ina most significant bit position of the first temporary result and secondtemporary result is repeated a number of times to convert the firsttemporary result and second temporary result to 64-bit values.
 17. Anon-transitory machine-readable medium, not being a signal per se,having program code stored thereon which, when executed by a machine,causes the machine to perform operations of: decoding a firstinstruction to generate a decoded instruction; storing a first pluralityof packed real and imaginary data elements in a first source register,the first plurality of packed real and imaginary data elementscomprising a first plurality of complex numbers; storing a secondplurality of packed real and imaginary data elements in a second sourceregister, the second plurality of packed real and imaginary dataelements comprising a second plurality of complex numbers, wherein eachof the second plurality of complex numbers comprises a complex conjugateof a corresponding complex number of the first plurality of complexnumbers; multiplying selected real and imaginary data elements in thefirst source register and the second source register includingmultiplying each selected imaginary data element in the first sourceregister with a selected real data element in the second source registerand multiplying each selected real data element in the first sourceregister with a selected imaginary data element in the second sourceregister to generate a plurality of imaginary products; adding a firstsubset of the plurality of imaginary products and subtracting a secondsubset of the plurality of imaginary products to generate a firsttemporary result and adding a third subset of the plurality of imaginaryproducts and subtracting a fourth subset of the plurality of imaginaryproducts to generate a second temporary result; accumulating the firsttemporary result with first data from a destination register to generatea first final result and accumulating the second temporary result withsecond data from the destination register to generate a second finalresult; and storing the first final result and the second final resultback in the destination register.
 18. The non-transitorymachine-readable medium of claim 17, wherein the first and secondplurality of packed real and imaginary data elements are stored as16-bit data elements in the first and second source registers, eachimaginary data element being stored in a data element location adjacentto a data element location of its corresponding real data element, eachcombination of a real and imaginary data element representing a complexnumber.
 19. The non-transitory machine-readable medium of claim 18,wherein the first and second source registers comprise 128-bit packeddata registers configurable with data element positions A, B, C, D, E,F, G, and H storing data elements A, B, C, D, E, F, G, and H,respectively, and wherein data elements A, C, E, and G are real dataelements and data elements B, D, F, and H are corresponding imaginarydata elements.
 20. The non-transitory machine-readable medium of claim19, wherein multiplying each selected imaginary data element in thefirst source register with a selected real data element in the secondsource register and multiplying each selected real data element in thefirst source register with a selected imaginary data element in thesecond source register to generate a plurality of imaginary productsfurther comprise: multiplying S1C*S2D, S1D*S2C, S1A*S2B, S1B*S2A,S1G*S2H, S1H*S2G, S1E*S2F, S1F*S2E to generate the plurality ofimaginary products, where S1 identifies the first source register, S2identifies the second source register and A-H identify the packed dataelements in data element positions A-H in the first and second sourceregisters, respectively.
 21. The non-transitory machine-readable mediumof claim 20, wherein adding of the first subset of the plurality ofimaginary products and subtracting of the second subset of the pluralityof imaginary products comprise S1C*S2D−S1D*S2C+S1A*S2B−S1B*S2A andadding of the third subset of the plurality of imaginary products andsubtracting of the fourth sub set of the plurality of imaginary productscomprise S1G*S2H−S1H*S2G+S1E*S2F−S1F*S2E to generate the first temporaryresult and second temporary result, respectively.
 22. The non-transitorymachine-readable medium of claim 21, wherein the operations furthercomprise: zero-extending or sign-extending the first and secondtemporary results to 64-bit values prior to accumulation with the firstand second data from the destination register, respectively.
 23. Thenon-transitory machine-readable medium of claim 22, wherein zeroes areadded to the first and second temporary results to convert the first andsecond temporary results to 64-bit values.
 24. The non-transitorymachine-readable medium of claim 22, wherein a value in a mostsignificant bit position of the first temporary result and secondtemporary result is repeated a number of times to convert the firsttemporary result and second temporary result to 64-bit values.